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A Comparative Study Between Hopfield Neural Network and A* Path Planning Algorithms for Mobile Robot

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Book cover Artificial Intelligence and Evolutionary Computations in Engineering Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 517))

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Abstract

Path planning is an important aspect of any mobile robot navigation to find a hazard-free path and an optimal path. Currently, the A* algorithm is considered to be one of the prominent algorithms for path planning in a known environment. However, with the rise of neural networks and machine learning, newer promising algorithms are emerging in this domain. Our work compares one such algorithm namely the Hopfield neural network-based path planning algorithm with A* in a static environment. Both the Hopfield network and the A* algorithm were implemented while minimizing the total run times of the programs. For this, both the algorithms were run in MATLAB environment and a set of mazes were then executed and their run times were compared. Based on the study, the A* algorithm fared better and the Hopfield network showed promising results with scope for further reduction in its run time.

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Author information

Authors and Affiliations

  1. School of Electrical and Electronics Engineering, VIT University, Chennai, India

    Suhit Atul Kodgule & Arka Das

  2. School of Mechanical and Building Sciences, VIT University, Chennai, India

    Arockia Doss Arockia Selvakumar

Authors
  1. Suhit Atul Kodgule
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  2. Arka Das
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  3. Arockia Doss Arockia Selvakumar
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Corresponding author

Correspondence to Arockia Doss Arockia Selvakumar .

Editor information

Editors and Affiliations

  1. Department of Electrical and Electronics Engineering, SRM University, Chennai, Tamil Nadu, India

    Subhransu Sekhar Dash

  2. Department of Electrical and Electronics Engineering, SRM University, Chennai, Tamil Nadu, India

    K. Vijayakumar

  3. Department of Electrical and Electronics Engineering, Indian Institute of Technology Delhi, New Delhi, India

    Bijaya Ketan Panigrahi

  4. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

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© 2017 Springer Nature Singapore Pte Ltd.

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Kodgule, S.A., Das, A., Arockia Selvakumar, A.D. (2017). A Comparative Study Between Hopfield Neural Network and A* Path Planning Algorithms for Mobile Robot. In: Dash, S., Vijayakumar, K., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-10-3174-8_4

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  • DOI: https://doi.org/10.1007/978-981-10-3174-8_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3173-1

  • Online ISBN: 978-981-10-3174-8

  • eBook Packages: EngineeringEngineering (R0)

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